• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.991-1002
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• 2014

Both Bayesian and maximum likelihood methods are efficient for the estimation of regression coefficients of various Tobit regression models (see. e.g. Chib, 1992; Greene, 1990; Lee and Choi, 2013); however, some researchers recognized that the maximum likelihood method tends to underestimate the disturbance variance, which has implications for the estimation of marginal effects and the asymptotic standard error of estimates. The underestimation of the maximum likelihood estimate in a seemingly unrelated Tobit regression model is examined. A Bayesian method based on an objective noninformative prior is shown to provide proper estimates of the disturbance variance as well as other regression parameters

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.83-92
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• 2014

Weather condition is one of the crucial factors affecting travelers' mode choice. Nevertheless, there are numerous indefinite traffic phenomena under various weather conditions. This study was conducted to verify the hypothesis that transit riderships decrease as precipitation increases. To clarify the relationship between precipitation and transit ridership, a seemingly unrelated regression model was employed with data such as daily precipitation and daily transit riderships of 3 transit modes (bus, metro, and shuttle bus) collected in Busan for recent 24 months. The estimation results show that transit riderships decreased as the daily precipitation increased when the daily precipitation is greater or equal to 10mm/day (0.169%, 0.101%, and 0.172% reduction in bus, metro, and shuttle bus riderships, respectively, when the daily precipitation increased by 1mm). When comparing the impact of precipitation on transit riderships by modes using a cross-equation parameter restriction test, the decrease in metro ridership is relatively insensitive to the change in precipitation. However, the negative coefficient of precipitation in the metro ridership estimation model indicates that the transit users in Busan may alter their mode to taxi or automobile and/or may give up the trip itself in bad weather condition.

• Journal of Korean Society of Forest Science
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• v.90 no.1
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• pp.1-9
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• 2001

The objectives of this study were to explain market structures of logs imported to Korea from U.S.A., New Zealand. Chile. The demand for imported logs is modeled as a function of output of wood manufacturing in Korea and log prices of competing suppliers. It is hypothesized that the quantity of log impaled in a period is determined by its own and competing prices and the output of wood corresponding manufacturing sector in the current period. Import demand functions of logs imported to Korea from U.S.A., New Zealand and Chile were estimated by SURE(Seemingly Unrelated Regression Equations). Elasticities of amounts of logs imported to Korea from U.S.A., New Zealand and Chile with respect to price of imported log from U.S.A. were -2.88, 1.36 and 3.17, respectively. Elasticities of amounts of logs imported to Korea from U.S.A., New Zealand and Chile with respect to price of imported log from New Zealand were 0.71, -1.65 and 1.44, respectively, Elasticities of amounts of logs imported to Korea from U.S.A., New Zealand and Chile with respect to price of imported log from Chile was -2.88. 1.36 and 3.17.

• Knowledge Management Research
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• v.23 no.2
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• pp.211-228
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• 2022

As social media marketing becomes prevalent, it is necessary to understand the administrative role of managers in promoting user engagement. However, little is known about how community managers enhance user engagement in social media. In this research, we study how managers can boost online user participation, including clicking likes and writing comments. Using the SUR (Seemingly Unrelated Regression) model, we find out that the active participation of managers increases user engagement of both passive (likes) and active (comments) ones. In addition, we find that the number of emotional words included in posts has a positive effect on the passive engagement whereas it negatively affects the active engagement. Lastly, the congruency between posts and comments positively affects users' passive engagement. This study contributes to prior literature related to online community management and text analyses. Furthermore, our findings offer managerial insights for practitioners and social media managers to further facilitate user engagement.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.180-191
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• 2020

This study analyzes factors that affect average daily travel time budgets, using the Time Use Survey data from 1999 to 2014 in Seoul. We first developed multivariate regression models for travel time from each year, considering demographic and socio-economic variables as well as non-home activity time. The model results showed that household and personal characteristics and non-home activities significantly affect travel time, and their effects are different over time. In addition, we developed seemingly unrelated regression (SUR) models for time allocation for non-home activity and travel, considering their correlations, and explanatory variables were compared over time. Overall, demographic and socio-economic variables significantly affect travel time as well as non-home activity time.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.237-245
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• 2003

MDS(multi-dimensional scaling) for preference data is a graphical tool which usually figures out how consumers recognize, evaluate certain products. This article is mainly concerned with an optimal scaling for MDS when target configuration is available. Rotation of axis and SUR(seemingly unrelated regression) methods are employed to get a new configuration which is obtained as close to the target as we can. Methodologies developed here are also illustrated via a real data set.

• Journal of Environmental Policy
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• v.9 no.4
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• pp.53-76
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• 2010

This paper attempts to estimate and compare environmental Kuznets curves (EKC) for$CO_2$ emissions of five regions constituting South Korea. For this, panel data of $CO_2$ emission for these regions are constucted for the period 1990 - 2007. Close inter-dependency among these five regions is considered by using a seemingly unrelated regression (SUR) model. In addition to real per-capita income, price index of energy sources and population dens ity are included as control variables. Results of estimates show the robust existence of EKC's in all these regions. EKC turning points of five regions range between 13.7 and 21.6 million Korean Won, showing a large variation. This difference among regions should be conisidered for the effective implementation of policies targeting the reduction of $CO_2$ emmission. In addition, the increase of energy price is found help reduce the $CO_2$ emmision while the rise of population density seems to lead to the increase of $CO_2$ emission.

• The Journal of the Korea Contents Association
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• v.11 no.1
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• pp.329-339
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• 2011

This study aims at investigating how English proficiency affects economic development of a country by analyzing the relationships among English proficiency, economic activities (amount of trade, R&D investment, etc), and the rate of economic growth, focusing on twenty-one non-English-speaking OECD countries. Ordinary Least Square (OLS) and Seemingly Unrelated Regression Estimation (SURE) were used for the data analysis in the study. The findings reveals that there existed little statistical significance to support the fact that English proficiency was directly related to the economic development in a positive way in many countries except Mexico, the Czech Republic, Finland, and Poland. However, English proficiency indirectly influenced the economic development in the way of increasing the amount of trade. These results can lead to the conclusion that English proficiency is not a sufficient element but a necessary one. Furthermore, it is expected that English proficiency can positively affect the economic development when it plays a part as sufficient complementary goods which make up for physical capital, technology accumulation, political stability, and worthy government.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.89-97
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• 2021

This study attempts to examine determinants of both digital capacity and digital utilization among older people by using the seemingly unrelated regression. Using '2019 Survey of Digital divide', the study has the following results: first, perceived usefulness, self-efficacy and confidence have significant relationship with digital capacity; second, not only self-efficacy and confidence but also digital support has significant relationship with digital utilization. By examining the common factors and differential factors which explain digital capacity and digital utilization, it contributes to broadening and deepening knowledge on digital divide and building effective strategies for overcoming digital divide among older people in Korea.

• Journal of Biosystems Engineering
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• v.31 no.3 s.116
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• pp.194-202
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• 2006

Using a multi-variable linear regression technique and SUR(seemingly unrelated regression) model, the demand functions of tractor, combine and rice transplanter were estimated. The demand was regarded as an annual supply of each machine and modeled as a function of 11 independent variables which reflect the actual farmer's income, actual prices of farm machines, previous supply, previous stock, actual amount of available subsidy, actual amount of available loan, arable land, import of farm machines and rice price. The actual amount of available loan affects most significantly the demand functions. The actual farmer's income, actual farmer's asset, loan coverage, and rice price affect the demand positively while prices of farm machines and import negatively. The annual demands of tractor, combine and rice transplanter estimated using the demand functions were also presented over the next 4 years.